Human Strongyloides stercoralis infection.

Strongyloides stercoralis is an important soil-transmitted helminth occurring world-wide and affecting 30-100 million people. Because many cases are asymptomatic and sensitive diagnostic methods are lacking, S. stercoralis infection is frequently underdiagnosed. The increasing incidence of autoimmune and wasting diseases and increased use of immunosuppressive agents, as well as the increased use of immunosuppressants and cytotoxic drugs, have increased S. stercoralis infection and their mortality. This review provides information about S. stercoralis epidemiology, life cycle, aetiology, pathology, comorbidities, immunology, vaccines, diagnosis, treatment, prevention, control and makes some recommendations for future prevention and control of this important parasite.

PGD 2 /DP1 axis promotes liver regeneration by secreting Wnt2 in KCs in mice.

BACKGROUND AND AIMS: The liver possesses a remarkable regenerative capacity in response to injuries or viral infections. Various growth factors and cytokines are involved in regulating liver regeneration. Prostaglandin D 2 , a pro-resolution lipid mediator, is the most abundant hepatic prostanoid. However, the role of prostaglandin D 2 in the injury-induced liver regeneration remains unclear. APPROACH AND RESULTS: Two-thirds partial hepatectomy (70% PH), massive hepatectomy (85% resection), and carbon tetrachloride-induced chronic injury were performed in mice to study the mechanisms of live regeneration. Hepatic prostaglandin D 2 production was elevated in mice after PH. Global deletion of D prostanoid receptor (DP) 1, but not DP2, slowed PH-induced liver regeneration in mice, as evidenced by lower liver weight to body weight ratio, less Ki67 + hepatocyte proliferation, and G2/M phase hepatocytes. In addition, DP1 deficiency, specifically in resident KCs, and not in endothelial cells or HSCs, retarded liver regeneration in mice after PH. Conversely, the overexpression of exogenous DP1 in KCs accelerated liver regeneration in mice. Mechanistically, DP1 activation promoted Wnt2 transcription in a PKA/CREB-dependent manner in resident KCs and mediated hepatocyte proliferation through Frizzled8/ß-catenin signaling. Adeno-associated virus vector serotype 8-mediated Frizzled8 knockdown in hepatocytes attenuated accelerated liver regeneration in KC-DP1 transgenic mice after PH. Treatment with the DP1 receptor agonist BW245C promotes PH-induced liver regeneration in mice. CONCLUSIONS: DP1 activation mediates crosstalk between KCs and hepatocytes through Wnt2 and facilitates liver regeneration. Hence, DP1 may serve as a novel therapeutic target in acute and chronic liver diseases.

Modelling the dynamic gas/particle partitioning process of semi-volatile organic compounds emitted from point sources: Quantitative analysis and impact assessment.

The deleterious impact of pollution point sources on the surrounding environment and human has long been a focal point of environmental research. When considering the local atmospheric dispersion of semi-volatile organic compounds (SVOCs) around the emission sites, it is essential to account the dynamic process for the gas/particle (G/P) partitioning, which involves the transition from an initial state to a steady state. In this study, we have developed a model that enables the prediction of the dynamic process for G/P partitioning of SVOCs, particularly considering the influence from emission. It is important to note that the dynamic processes of the concentrations of SVOCs in particle phase (CP) and in gas phase (CG) differ significantly. These differences arise due to the influence of two critical factors: particulate proportion of SVOCs in the emissions (ϕ0) and octanol-air partitioning coefficient (KOA). The validity of our model was assessed by comparing its predictions of the extremum value of the G/P partitioning quotient (KP) with the results obtained from the steady-state model. Remarkably, the characteristic time (tC), used to evaluate the timescale required for SVOCs to reach steady state, demonstrated different variations with KOA for CP and CG. Additionally, the values of tC were quite different for CP and CG, which were markedly influenced by ϕ0. For some SVOCs with high KOA values, it took approximately 35 h to reach steady state. Furthermore, it was found that the time to achieve 95 % of steady state (t95 ≈ 3tC) could reach approximately 105 h. This duration is sufficient for chemicals to disperse from their emission site to the surrounding areas. Therefore, it is crucial to consider the dynamic process of G/P partitioning in local atmospheric transport studies. Moreover, the influence of ϕ0 should be incorporated into future investigations examining the dynamic process of G/P partitioning.

Clinicopathologic analysis of nodal T-follicular helper cell lymphomas, a multicenter retrospective study from China.

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

IL-2 promotes expansion and intratumoral accumulation of tumor infiltrating dendritic cells in pancreatic cancer.

This study aims to investigate the diagnostic potential of IL-2 for PDAC and develop a method to improve the dendritic cell (DC) based vaccine against PDAC. The gene expression data and clinical characteristics information for 178 patients with PDAC were obtained from The Cancer Genome Atlas (TCGA). DCs were isolated from Human peripheral blood mononuclear cells (PBMCs) and were cultured in 4 different conditions. DCs were pulsed by tumor cell lysates or KRAS G12D1 - 23 peptide, and then used to activate T cells. The mixture of DCs and T cells were administered to xenograft mouse model through the tail vein. The infiltration of DCs and T cells were detected by immunohistochemistry. The generation of KRAS G12D mutation specific cytotoxic T cells was determined by in vitro killing assay. We observed that PDAC patients with higher IL-2 mRNA levels exhibited improved overall survival and increased infiltration of CD8 + T cells, NK cells, naïve B cells, and resting myeloid DCs in the tumor microenvironment. IL-2 alone did not enhance DC proliferation, antigen uptake, or apoptosis inhibition unless co-cultured with PBMCs. DCs co-cultured with PBMCs in IL-2-containing medium demonstrated the strongest tumor repression effect in vitro and in vivo. Compared to DCs obtained through the traditional method (cultured in medium containing GM-CSF and IL-4), DCs cultured with PBMCs, and IL-2 exhibited increased tumor infiltration capacity, potentially facilitating sustained T cell immunity. DCs cultured in the PBMCs-IL-2 condition could promote the generation of cytotoxic T cells targeting tumor cells carrying KRAS G12D mutation.

Schistosome egg-derived extracellular vesicles deliver Sja-miR-71a inhibits host macrophage and neutrophil extracellular traps via targeting Sema4D.

BACKGROUND: Macrophages and neutrophils are rapidly recruited around Schistosome eggs to form granulomas. Extracellular traps (ETs) of macrophages and neutrophils are part of the pathogen clearance armamentarium of leukocytes. Schistosome eggs possess the ability to resist attack by the host's immune cells and survive by employing various immune evasion mechanisms, including the release of extracellular vesicles (EVs). However, the specific mechanisms by which Schistosome egg-derived EVs (E-EVs) evade the immune response and resist attack from macrophage and neutrophil ETs remain poorly understood. In this study, we aimed to investigate the association between E-EVs and macrophage/neutrophil ETs. METHODS: EVs were isolated from the culture supernatant of S. japonicum eggs and treated macrophages and neutrophils with E-EVs and Sja-miR-71a. The formation of ETs was then observed. Additionally, we infected mice with S. japonicum, administered HBAAV2/9-Sja-miR-71a, and the formation of macrophage ETs (METs) and neutrophil ETs (NETs) in the livers was measured. Sema4D-knockout mice, RNA sequencing, and trans-well assay were used to clarify Sja-miR-71a in E-EVs inhibits METs and NETs formation via the Sema4D/ PPAR-γ/ IL-10 axis. RESULTS: Our findings revealed that E-EVs were internalized by macrophages and neutrophils, leading to the inhibition of METs and NETs formation. The highly expressed Sja-miR-71a in E-EVs targeted Sema4D, resulting in the up-regulation of IL-10 and subsequent inhibition of METs and NETs formation. Sema4D knockout up-regulated IL-10 expression and inhibited the formation of METs and NETs. Furthermore, we further demonstrated that Sja-miR-71a inhibits METs and NETs formation via the Sema4D/ PPAR-γ/ IL-10 axis. CONCLUSIONS: In summary, our findings provide new insights into the immune evasion abilities of Schistosome eggs by demonstrating their ability to inhibit the formation of METs and NETs through the secretion of EVs. This study enhances our understanding of the host-pathogen interaction and may have implications for the development of novel therapeutic approaches. Video Abstract.

Optical design of a reflective double-grating spectrometer to detect one branch in the pure rotational Raman spectrum of N2.

This paper presents the optical design of a high-resolution double-grating spectrometer for extracting the multiple lines in the Stokes or anti-Stokes branch of the pure rotational Raman spectra of nitrogen. The spectrometer is composed of collimating and focusing mirrors, two reflective gratings, and a linear detector. The structural parameters were calculated using geometric configuration, dispersion, and aberrational theory, and conditions for first-order correction of keystone distortion with divergent grating illumination were derived. Based on this method, we simulated a spectrometer with a 16-channel linear array photomultiplier tube, resulting in uniformly distributed single-branch lines on each detector channel. The resolution reached 0.225 nm per channel, and the keystone distortion was less than 0.7%. The spectrometer avoids the interference of elastic signals by not detecting them, enabling the extraction of atmospheric temperature profiles via separated single-branch lines with high precision. Our design provides a promising solution to extract atmospheric temperature profiles for pure rotational Raman lidar.

Knockout of Sema4D alleviates liver fibrosis by suppressing AOX1 expression.

Liver fibrosis can occur in many chronic liver diseases, and no effective treatments are available due to the poorly characterized molecular pathogenesis. Semaphorin 4D (Sema4D) has immune functions and serves important roles in T cell priming. Here, we found that Sema4D was highly expressed in fibrotic liver, and the expression of Sema4D increased with hepatic stellate cells (HSCs) activation. Knockout of Sema4D alleviated liver fibrosis. Mechanistically, knockout of Sema4D alleviated liver fibrosis by suppressing the expression of AOX1 in retinol metabolism. Further investigation demonstrated that retinoic acid receptor α (RARA), an important nuclear receptor of retinoic acid, was reduced by Sema4D knockout during liver fibrogenesis. Sema4D knockout-mediated suppression of liver fibrosis was partly mediated by regulating the balance of Th1, Th2, Th17, and T-bet+Treg cells via inhibiting AOX1/RARA. Thus, targeting Sema4D may hold promise as a potential therapeutic approach for treating liver fibrosis.

Aminoacyl-tRNA Synthetase-based Prognosis Model and Exploration of Potential Mechanisms in Hepatocellular Carcinoma.

Background and Aims: Aminoacyl-tRNA synthetases (ARSs) participate in tumor initiation and progression but their involvement in hepatocellular carcinoma (HCC) is not clear. This study aimed to investigate the prognostic value and underlying mechanisms of ARS in HCC. Methods: Data were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, Gene Expression Omnibus and Human Protein Atlas databases. The prognostic model was constructed with the use of Cox regression and least absolute shrinkage and selection operator regression. Kaplan-Meier survival analysis, enrichment analysis, single sample gene set enrichment analysis and tumor mutation burden calculation were performed with R to evaluate the model and explore the underlying mechanism. Wilcoxon tests were used for comparisons between groups. Results: Aspartyl-tRNA synthetase 2 (DARS2), tyrosyl-tRNA synthetase 1 (YARS1) and cysteinyl-tRNA synthetase 2 (CARS2) were identified as prognostic biomarkers and enrolled in model construction. The area under receiver operating characteristic curve of the model was 0.775. The model was used to assign patients from TCGA into low- and high-risk groups. Those in the high-risk group had a worse prognosis (p<0.001). The clinical significance of the model was tested in different clinical subgroups. Genetic mutation analysis had a higher TP53 mutation frequency in high-risk group. Enrichment analysis and study of immune-related cells and molecules found that the high-risk group was characterized by immune-cell infiltration and immunosuppression states. Conclusions: A novel ARS family-based model of HCC prognosis was constructed. TP53 mutation frequency and immune-suppressive status accounted for a worse prognosis in patients included in the high-risk group.

Convolutional neural network-based segmentation network applied to image recognition of angiodysplasias lesion under capsule endoscopy.

BACKGROUND: Small intestinal vascular malformations (angiodysplasias) are common causes of small intestinal bleeding. While capsule endoscopy has become the primary diagnostic method for angiodysplasia, manual reading of the entire gastrointestinal tract is time-consuming and requires a heavy workload, which affects the accuracy of diagnosis. AIM: To evaluate whether artificial intelligence can assist the diagnosis and increase the detection rate of angiodysplasias in the small intestine, achieve automatic disease detection, and shorten the capsule endoscopy (CE) reading time. METHODS: A convolutional neural network semantic segmentation model with a feature fusion method, which automatically recognizes the category of vascular dysplasia under CE and draws the lesion contour, thus improving the efficiency and accuracy of identifying small intestinal vascular malformation lesions, was proposed. Resnet-50 was used as the skeleton network to design the fusion mechanism, fuse the shallow and depth features, and classify the images at the pixel level to achieve the segmentation and recognition of vascular dysplasia. The training set and test set were constructed and compared with PSPNet, Deeplab3+, and UperNet. RESULTS: The test set constructed in the study achieved satisfactory results, where pixel accuracy was 99%, mean intersection over union was 0.69, negative predictive value was 98.74%, and positive predictive value was 94.27%. The model parameter was 46.38 M, the float calculation was 467.2 G, and the time length to segment and recognize a picture was 0.6 s. CONCLUSION: Constructing a segmentation network based on deep learning to segment and recognize angiodysplasias lesions is an effective and feasible method for diagnosing angiodysplasias lesions.